In addition to human, close reading of student text with rubrics for assessment, educators use nonhuman, distant computer-assisted tools to help quantitatively measure otherwise qualitative keywords to prevent bias in grading and help read beyond the sentence for underlying cognitions. We apply the Linguistic Inquiry and Word Count (LIWC) software tool to analyze different forms of student writing used in STEM education and research to assess writing of native English speakers and non-native English Language Learners (ELLs), including international students. Available in several languages, LIWC measures four summary variables, Analytical Thinking, Clout, Authentic, and Emotional Tone, to provide outputs as raw word counts, as percentages of words used relative to the text compared with a dictionary of words in categories and sub-dictionaries, and as scores correlating these words algorithmically based on a dictionary of terms associated with underlying meanings. This tool can help measure student personal reflective writing for underlying psychosocial indicators or the cognitive and analytical process in other science writing. By selecting key variables, or creating a personal dictionary, LIWC can be used to analyze scientific writing to detect progressive development of student analytical writing from early draft to final version for different informal and formal writing styles. We share methods, examples, and the potential for using LIWC measures of cognitive processes for different measures of student writing in science courses.
PubMed: MeSH publication types
- Journal Article